Overview

Dataset statistics

Number of variables11
Number of observations590
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory55.3 KiB
Average record size in memory96.0 B

Variable types

Numeric11

Alerts

Ages[15-49]_All_grade1 is highly overall correlated with Ages[15-49]_All_grade2 and 7 other fieldsHigh correlation
Ages[15-49]_All_grade2 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_All_grade3 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Male_grade1 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Male_grade2 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Male_grade3 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Female_grade1 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Female_grade2 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation
Ages[15-49]_Female_grade3 is highly overall correlated with Ages[15-49]_All_grade1 and 7 other fieldsHigh correlation

Reproduction

Analysis started2023-11-05 14:41:49.358307
Analysis finished2023-11-05 14:42:10.777848
Duration21.42 seconds
Software versionydata-profiling vv4.6.1
Download configurationconfig.json

Variables

country
Real number (ℝ)

Distinct129
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.466102
Minimum0
Maximum128
Zeros3
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:10.920990image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.45
Q132.25
median63
Q393
95-th percentile123
Maximum128
Range128
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation35.965151
Coefficient of variation (CV)0.56668284
Kurtosis-1.1089292
Mean63.466102
Median Absolute Deviation (MAD)30.5
Skewness0.048253334
Sum37445
Variance1293.4921
MonotonicityNot monotonic
2023-11-05T15:42:11.164733image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 12
 
2.0%
46 11
 
1.9%
108 11
 
1.9%
123 10
 
1.7%
23 10
 
1.7%
54 10
 
1.7%
14 9
 
1.5%
107 9
 
1.5%
127 9
 
1.5%
91 9
 
1.5%
Other values (119) 490
83.1%
ValueCountFrequency (%)
0 3
 
0.5%
1 4
 
0.7%
2 1
 
0.2%
3 4
 
0.7%
4 4
 
0.7%
5 2
 
0.3%
6 12
2.0%
7 2
 
0.3%
8 2
 
0.3%
9 7
1.2%
ValueCountFrequency (%)
128 8
1.4%
127 9
1.5%
126 1
 
0.2%
125 1
 
0.2%
124 4
 
0.7%
123 10
1.7%
122 4
 
0.7%
121 1
 
0.2%
120 3
 
0.5%
119 1
 
0.2%

year
Real number (ℝ)

Distinct34
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.1932
Minimum1981
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:11.405896image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1981
5-th percentile1992
Q12000
median2005
Q32011.75
95-th percentile2018
Maximum2020
Range39
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation8.013568
Coefficient of variation (CV)0.0039964069
Kurtosis-0.82138526
Mean2005.1932
Median Absolute Deviation (MAD)6
Skewness-0.076786051
Sum1183064
Variance64.217271
MonotonicityIncreasing
2023-11-05T15:42:11.631792image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2000 50
 
8.5%
2005 40
 
6.8%
2006 36
 
6.1%
2010 28
 
4.7%
2014 25
 
4.2%
2011 24
 
4.1%
2019 23
 
3.9%
2018 22
 
3.7%
2012 22
 
3.7%
2001 22
 
3.7%
Other values (24) 298
50.5%
ValueCountFrequency (%)
1981 1
 
0.2%
1985 1
 
0.2%
1989 4
 
0.7%
1990 8
 
1.4%
1991 10
1.7%
1992 13
2.2%
1993 11
1.9%
1994 13
2.2%
1995 15
2.5%
1996 20
3.4%
ValueCountFrequency (%)
2020 2
 
0.3%
2019 23
3.9%
2018 22
3.7%
2017 9
 
1.5%
2016 13
2.2%
2015 16
2.7%
2014 25
4.2%
2013 16
2.7%
2012 22
3.7%
2011 24
4.1%

Ages[15-49]_All_grade1
Real number (ℝ)

HIGH CORRELATION 

Distinct586
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.87386538
Minimum0.25191653
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:11.871409image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.25191653
5-th percentile0.50203451
Q10.82592559
median0.94971344
Q30.98491488
95-th percentile0.9961109
Maximum1
Range0.74808347
Interquartile range (IQR)0.1589893

Descriptive statistics

Standard deviation0.16280998
Coefficient of variation (CV)0.18631013
Kurtosis2.796587
Mean0.87386538
Median Absolute Deviation (MAD)0.043760031
Skewness-1.8024839
Sum515.58058
Variance0.026507089
MonotonicityNot monotonic
2023-11-05T15:42:12.121170image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
0.7%
0.8710972071 2
 
0.3%
0.4780151248 1
 
0.2%
0.9917046428 1
 
0.2%
0.9893835783 1
 
0.2%
0.8940396905 1
 
0.2%
0.965524435 1
 
0.2%
0.916691184 1
 
0.2%
0.8248852491 1
 
0.2%
0.562609911 1
 
0.2%
Other values (576) 576
97.6%
ValueCountFrequency (%)
0.2519165277 1
0.2%
0.2675411105 1
0.2%
0.2743234634 1
0.2%
0.2803148031 1
0.2%
0.2880326807 1
0.2%
0.2919573486 1
0.2%
0.2934274077 1
0.2%
0.294970125 1
0.2%
0.3171576262 1
0.2%
0.3236398697 1
0.2%
ValueCountFrequency (%)
1 4
0.7%
0.9998298287 1
 
0.2%
0.9997598529 1
 
0.2%
0.9992375374 1
 
0.2%
0.998536706 1
 
0.2%
0.9983882904 1
 
0.2%
0.9981418252 1
 
0.2%
0.9980663657 1
 
0.2%
0.9980211854 1
 
0.2%
0.9979032874 1
 
0.2%

Ages[15-49]_All_grade2
Real number (ℝ)

HIGH CORRELATION 

Distinct589
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86174093
Minimum0.24407127
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:12.359327image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.24407127
5-th percentile0.48072845
Q10.80183934
median0.93790281
Q30.98036033
95-th percentile0.99450131
Maximum1
Range0.75592873
Interquartile range (IQR)0.17852099

Descriptive statistics

Standard deviation0.16702206
Coefficient of variation (CV)0.19381934
Kurtosis2.3253964
Mean0.86174093
Median Absolute Deviation (MAD)0.052507579
Skewness-1.6755924
Sum508.42715
Variance0.027896369
MonotonicityNot monotonic
2023-11-05T15:42:12.738235image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8423897028 2
 
0.3%
0.9938547611 1
 
0.2%
0.9845506549 1
 
0.2%
0.876758039 1
 
0.2%
0.9532709122 1
 
0.2%
0.912440598 1
 
0.2%
0.8015320301 1
 
0.2%
0.4651584029 1
 
0.2%
0.5447955728 1
 
0.2%
0.7629928589 1
 
0.2%
Other values (579) 579
98.1%
ValueCountFrequency (%)
0.244071275 1
0.2%
0.2617967129 1
0.2%
0.26510185 1
0.2%
0.2713519633 1
0.2%
0.2782647014 1
0.2%
0.2859278917 1
0.2%
0.2865097225 1
0.2%
0.2880326807 1
0.2%
0.3047781587 1
0.2%
0.3124300241 1
0.2%
ValueCountFrequency (%)
1 1
0.2%
0.9997598529 1
0.2%
0.9995408654 1
0.2%
0.9992375374 1
0.2%
0.9991862774 1
0.2%
0.9991492033 1
0.2%
0.9983882904 1
0.2%
0.9981418252 1
0.2%
0.9980663657 1
0.2%
0.997951448 1
0.2%

Ages[15-49]_All_grade3
Real number (ℝ)

HIGH CORRELATION 

Distinct589
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83824716
Minimum0.23327357
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:12.974494image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.23327357
5-th percentile0.45220508
Q10.75920968
median0.91314662
Q30.97241184
95-th percentile0.99352823
Maximum1
Range0.76672643
Interquartile range (IQR)0.21320216

Descriptive statistics

Standard deviation0.17668559
Coefficient of variation (CV)0.21077982
Kurtosis1.4694289
Mean0.83824716
Median Absolute Deviation (MAD)0.071630508
Skewness-1.4371264
Sum494.56582
Variance0.031217797
MonotonicityNot monotonic
2023-11-05T15:42:13.197787image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7827367187 2
 
0.3%
0.9920349717 1
 
0.2%
0.9766504169 1
 
0.2%
0.8430896401 1
 
0.2%
0.9228249192 1
 
0.2%
0.899305582 1
 
0.2%
0.7448367476 1
 
0.2%
0.442728132 1
 
0.2%
0.5102220774 1
 
0.2%
0.7107812166 1
 
0.2%
Other values (579) 579
98.1%
ValueCountFrequency (%)
0.2332735658 1
0.2%
0.2465851754 1
0.2%
0.2524287999 1
0.2%
0.2550808787 1
0.2%
0.2564779818 1
0.2%
0.2600584328 1
0.2%
0.2625986636 1
0.2%
0.2767798603 1
0.2%
0.2866811752 1
0.2%
0.2912916541 1
0.2%
ValueCountFrequency (%)
1 1
0.2%
0.9997598529 1
0.2%
0.9995408654 1
0.2%
0.9992375374 1
0.2%
0.9991862774 1
0.2%
0.9981418252 1
0.2%
0.9980663657 1
0.2%
0.997951448 1
0.2%
0.9974088669 1
0.2%
0.9973631501 1
0.2%

Ages[15-49]_Male_grade1
Real number (ℝ)

HIGH CORRELATION 

Distinct583
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.89490043
Minimum0.3170841
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:13.438910image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.3170841
5-th percentile0.60689274
Q10.86612775
median0.95173404
Q30.98544969
95-th percentile0.99579228
Maximum1
Range0.6829159
Interquartile range (IQR)0.11932193

Descriptive statistics

Standard deviation0.13657656
Coefficient of variation (CV)0.15261649
Kurtosis4.0688877
Mean0.89490043
Median Absolute Deviation (MAD)0.040158302
Skewness-2.0298373
Sum527.99125
Variance0.018653157
MonotonicityNot monotonic
2023-11-05T15:42:13.675883image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7
 
1.2%
0.9193992615 2
 
0.3%
0.9791212082 1
 
0.2%
0.6585125923 1
 
0.2%
0.9861204028 1
 
0.2%
0.930719614 1
 
0.2%
0.9704806805 1
 
0.2%
0.9284552932 1
 
0.2%
0.8846905231 1
 
0.2%
0.5243108869 1
 
0.2%
Other values (573) 573
97.1%
ValueCountFrequency (%)
0.3170841038 1
0.2%
0.3227265477 1
0.2%
0.3361186683 1
0.2%
0.3570645154 1
0.2%
0.3645169735 1
0.2%
0.3852404356 1
0.2%
0.3878842592 1
0.2%
0.3884650469 1
0.2%
0.3926050365 1
0.2%
0.3927299678 1
0.2%
ValueCountFrequency (%)
1 7
1.2%
0.9995279908 1
 
0.2%
0.9993175268 1
 
0.2%
0.9992207289 1
 
0.2%
0.9985312819 1
 
0.2%
0.998318851 1
 
0.2%
0.9982489347 1
 
0.2%
0.9981643558 1
 
0.2%
0.9974814355 1
 
0.2%
0.9974358678 1
 
0.2%

Ages[15-49]_Male_grade2
Real number (ℝ)

HIGH CORRELATION 

Distinct585
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.88204892
Minimum0.31467757
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:13.942980image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.31467757
5-th percentile0.57709967
Q10.83663058
median0.93966965
Q30.98078333
95-th percentile0.9937563
Maximum1
Range0.68532243
Interquartile range (IQR)0.14415275

Descriptive statistics

Standard deviation0.14129379
Coefficient of variation (CV)0.16018815
Kurtosis3.3367891
Mean0.88204892
Median Absolute Deviation (MAD)0.048633814
Skewness-1.8547686
Sum520.40886
Variance0.019963935
MonotonicityNot monotonic
2023-11-05T15:42:14.164874image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
0.7%
0.899446547 2
 
0.3%
0.9937888384 2
 
0.3%
0.9800996184 1
 
0.2%
0.9183135033 1
 
0.2%
0.9565074444 1
 
0.2%
0.9224660993 1
 
0.2%
0.8627933264 1
 
0.2%
0.5137627125 1
 
0.2%
0.6377453804 1
 
0.2%
Other values (575) 575
97.5%
ValueCountFrequency (%)
0.3146775663 1
0.2%
0.3158782125 1
0.2%
0.3224535882 1
0.2%
0.3381987214 1
0.2%
0.3433669806 1
0.2%
0.344794482 1
0.2%
0.3772052228 1
0.2%
0.3820918202 1
0.2%
0.383697927 1
0.2%
0.3869318068 1
0.2%
ValueCountFrequency (%)
1 4
0.7%
0.9995279908 1
 
0.2%
0.9992207289 1
 
0.2%
0.9990741014 1
 
0.2%
0.9990300536 1
 
0.2%
0.9987632632 1
 
0.2%
0.9985312819 1
 
0.2%
0.998318851 1
 
0.2%
0.9982489347 1
 
0.2%
0.9971903563 1
 
0.2%

Ages[15-49]_Male_grade3
Real number (ℝ)

HIGH CORRELATION 

Distinct587
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.85711494
Minimum0.27713883
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:14.403535image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.27713883
5-th percentile0.5317959
Q10.79009627
median0.91352203
Q30.97224522
95-th percentile0.99306207
Maximum1
Range0.72286117
Interquartile range (IQR)0.18214895

Descriptive statistics

Standard deviation0.15205347
Coefficient of variation (CV)0.17740149
Kurtosis2.0814615
Mean0.85711494
Median Absolute Deviation (MAD)0.069919825
Skewness-1.5379445
Sum505.69781
Variance0.023120258
MonotonicityNot monotonic
2023-11-05T15:42:14.615585image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
0.5%
0.840878427 2
 
0.3%
0.8493292332 1
 
0.2%
0.9701475501 1
 
0.2%
0.8896198273 1
 
0.2%
0.9233191013 1
 
0.2%
0.9058679342 1
 
0.2%
0.8047410846 1
 
0.2%
0.4901646078 1
 
0.2%
0.602578342 1
 
0.2%
Other values (577) 577
97.8%
ValueCountFrequency (%)
0.2771388292 1
0.2%
0.3006979227 1
0.2%
0.3042455316 1
0.2%
0.3064506352 1
0.2%
0.3200441301 1
0.2%
0.3216159344 1
0.2%
0.3519760668 1
0.2%
0.3533827066 1
0.2%
0.3614393771 1
0.2%
0.3694065511 1
0.2%
ValueCountFrequency (%)
1 3
0.5%
0.9995279908 1
 
0.2%
0.9992207289 1
 
0.2%
0.9990741014 1
 
0.2%
0.9985312819 1
 
0.2%
0.998318851 1
 
0.2%
0.9982489347 1
 
0.2%
0.9971903563 1
 
0.2%
0.9967224002 1
 
0.2%
0.996450901 1
 
0.2%

Ages[15-49]_Female_grade1
Real number (ℝ)

HIGH CORRELATION 

Distinct581
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.85320958
Minimum0.16565166
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:14.831891image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.16565166
5-th percentile0.40911005
Q10.79762669
median0.95129129
Q30.9859381
95-th percentile0.99788346
Maximum1
Range0.83434834
Interquartile range (IQR)0.18831141

Descriptive statistics

Standard deviation0.19251109
Coefficient of variation (CV)0.22563166
Kurtosis1.9833048
Mean0.85320958
Median Absolute Deviation (MAD)0.044643402
Skewness-1.6548639
Sum503.39365
Variance0.037060521
MonotonicityNot monotonic
2023-11-05T15:42:15.050752image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
1.5%
0.8230339885 2
 
0.3%
0.4686522484 1
 
0.2%
0.9925284982 1
 
0.2%
0.8514429331 1
 
0.2%
0.9603136182 1
 
0.2%
0.9039958119 1
 
0.2%
0.774079144 1
 
0.2%
0.4298371375 1
 
0.2%
0.6832026243 1
 
0.2%
Other values (571) 571
96.8%
ValueCountFrequency (%)
0.1656516641 1
0.2%
0.1808767766 1
0.2%
0.1944844425 1
0.2%
0.2062006891 1
0.2%
0.2071643323 1
0.2%
0.2126361877 1
0.2%
0.219355002 1
0.2%
0.2283948809 1
0.2%
0.2371551096 1
0.2%
0.2412475795 1
0.2%
ValueCountFrequency (%)
1 9
1.5%
0.9999153018 1
 
0.2%
0.9996408224 1
 
0.2%
0.9995087981 1
 
0.2%
0.9992818236 1
 
0.2%
0.999263823 1
 
0.2%
0.9992578626 1
 
0.2%
0.9991359711 1
 
0.2%
0.9990851283 1
 
0.2%
0.9988521934 1
 
0.2%

Ages[15-49]_Female_grade2
Real number (ℝ)

HIGH CORRELATION 

Distinct584
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.84181593
Minimum0.16565166
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:15.264005image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.16565166
5-th percentile0.38907952
Q10.7725683
median0.93936217
Q30.98281975
95-th percentile0.99681495
Maximum1
Range0.83434834
Interquartile range (IQR)0.21025145

Descriptive statistics

Standard deviation0.19651618
Coefficient of variation (CV)0.23344317
Kurtosis1.6478791
Mean0.84181593
Median Absolute Deviation (MAD)0.054529279
Skewness-1.5559652
Sum496.6714
Variance0.038618609
MonotonicityNot monotonic
2023-11-05T15:42:15.488960image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
1.0%
0.785615027 2
 
0.3%
0.4145779908 1
 
0.2%
0.9905053377 1
 
0.2%
0.988840282 1
 
0.2%
0.8284993768 1
 
0.2%
0.9498681426 1
 
0.2%
0.9016214013 1
 
0.2%
0.7494890094 1
 
0.2%
0.4537309706 1
 
0.2%
Other values (574) 574
97.3%
ValueCountFrequency (%)
0.1656516641 1
0.2%
0.1720313728 1
0.2%
0.1885119081 1
0.2%
0.2012457699 1
0.2%
0.2018099427 1
0.2%
0.2020214796 1
0.2%
0.2145776004 1
0.2%
0.2168838978 1
0.2%
0.2342349887 1
0.2%
0.2346676439 1
0.2%
ValueCountFrequency (%)
1 6
1.0%
0.9994249344 1
 
0.2%
0.9993582368 1
 
0.2%
0.9992818236 1
 
0.2%
0.9992815852 1
 
0.2%
0.999263823 1
 
0.2%
0.9992578626 1
 
0.2%
0.9991359711 1
 
0.2%
0.9990851283 1
 
0.2%
0.9990175962 1
 
0.2%

Ages[15-49]_Female_grade3
Real number (ℝ)

HIGH CORRELATION 

Distinct585
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.81978273
Minimum0.15985909
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.2 KiB
2023-11-05T15:42:15.851046image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.15985909
5-th percentile0.36944628
Q10.72499667
median0.91201454
Q30.97650531
95-th percentile0.9962085
Maximum1
Range0.84014091
Interquartile range (IQR)0.25150864

Descriptive statistics

Standard deviation0.20553043
Coefficient of variation (CV)0.2507133
Kurtosis1.0295619
Mean0.81978273
Median Absolute Deviation (MAD)0.076907665
Skewness-1.3693383
Sum483.67181
Variance0.042242757
MonotonicityNot monotonic
2023-11-05T15:42:16.078016image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
0.8%
0.7248824239 2
 
0.3%
0.4197389483 1
 
0.2%
0.9829174876 1
 
0.2%
0.7890537977 1
 
0.2%
0.9223053455 1
 
0.2%
0.8922237754 1
 
0.2%
0.6939466 1
 
0.2%
0.3933630288 1
 
0.2%
0.5988471508 1
 
0.2%
Other values (575) 575
97.5%
ValueCountFrequency (%)
0.159859091 1
0.2%
0.1654021144 1
0.2%
0.1735449433 1
0.2%
0.1855382025 1
0.2%
0.1890255213 1
0.2%
0.1923484653 1
0.2%
0.1941232234 1
0.2%
0.1949039996 1
0.2%
0.2054816931 1
0.2%
0.2169087827 1
0.2%
ValueCountFrequency (%)
1 5
0.8%
0.9994249344 1
 
0.2%
0.999263823 1
 
0.2%
0.9992578626 1
 
0.2%
0.9991359711 1
 
0.2%
0.9991348386 1
 
0.2%
0.9990851283 1
 
0.2%
0.9990175962 1
 
0.2%
0.9988521934 1
 
0.2%
0.9988068938 1
 
0.2%

Interactions

2023-11-05T15:42:08.604464image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:49.596627image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:51.438086image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.590812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.417856image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:57.261921image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.169874image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.231179image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.245629image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.087969image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.776021image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:08.761009image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:49.749679image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:51.635812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.744479image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.604361image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:57.550340image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.311786image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.392993image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.405463image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.236546image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.926352image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:08.935573image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:49.912784image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:51.831460image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.924038image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.767287image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:57.732561image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.478786image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.559813image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.625566image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.396760image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.082355image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.091753image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.078657image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:52.059422image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.095535image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.926368image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:57.895672image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.638682image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.717761image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.802480image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.556893image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.249054image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.244243image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.237079image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:52.321917image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.266524image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.088749image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.058495image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.810523image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.921623image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.979532image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.711852image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.411170image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.402976image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.401936image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:52.604906image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.449092image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.291216image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.227516image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.983485image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:02.096363image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.152011image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:05.879227image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.575012image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.568268image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.578361image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:52.775226image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.616749image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.458216image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.383779image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:00.145337image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:02.265332image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.319185image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.038532image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.735128image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.715041image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.749821image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:52.950547image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.796128image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.623047image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.549444image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:00.411156image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:02.423288image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.484472image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.195927image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:07.888407image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:09.870602image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:50.937676image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.120469image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:54.957826image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.791906image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.717111image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:00.726113image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:02.599293image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.641989image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.353403image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:08.050408image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:10.020031image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:51.110185image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.282497image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.111934image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:56.951928image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:58.874339image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:00.871842image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:02.937268image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.793082image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.502702image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:08.185940image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:10.169907image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:51.279051image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:53.433456image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:55.267873image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:57.100423image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:41:59.024904image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:01.022345image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:03.089542image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:04.947904image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:06.633115image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-05T15:42:08.336254image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2023-11-05T15:42:16.246428image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
countryyearAges[15-49]_All_grade1Ages[15-49]_All_grade2Ages[15-49]_All_grade3Ages[15-49]_Male_grade1Ages[15-49]_Male_grade2Ages[15-49]_Male_grade3Ages[15-49]_Female_grade1Ages[15-49]_Female_grade2Ages[15-49]_Female_grade3
country1.0000.0580.1470.1630.1740.1670.1820.1880.1260.1410.157
year0.0581.0000.1870.2020.2180.1730.1920.2090.1930.2070.223
Ages[15-49]_All_grade10.1470.1871.0000.9920.9780.9810.9710.9530.9880.9830.974
Ages[15-49]_All_grade20.1630.2020.9921.0000.9940.9760.9820.9720.9790.9880.986
Ages[15-49]_All_grade30.1740.2180.9780.9941.0000.9650.9800.9830.9640.9790.988
Ages[15-49]_Male_grade10.1670.1730.9810.9760.9651.0000.9900.9720.9420.9400.935
Ages[15-49]_Male_grade20.1820.1920.9710.9820.9800.9901.0000.9920.9330.9440.947
Ages[15-49]_Male_grade30.1880.2090.9530.9720.9830.9720.9921.0000.9160.9340.947
Ages[15-49]_Female_grade10.1260.1930.9880.9790.9640.9420.9330.9161.0000.9940.982
Ages[15-49]_Female_grade20.1410.2070.9830.9880.9790.9400.9440.9340.9941.0000.995
Ages[15-49]_Female_grade30.1570.2230.9740.9860.9880.9350.9470.9470.9820.9951.000

Missing values

2023-11-05T15:42:10.380686image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-11-05T15:42:10.658707image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

countryyearAges[15-49]_All_grade1Ages[15-49]_All_grade2Ages[15-49]_All_grade3Ages[15-49]_Male_grade1Ages[15-49]_Male_grade2Ages[15-49]_Male_grade3Ages[15-49]_Female_grade1Ages[15-49]_Female_grade2Ages[15-49]_Female_grade3
551419810.8749980.8351510.7692220.8565800.8127630.7453370.8935220.8576680.793244
561419850.8926310.8536850.7891420.8695580.8253950.7568390.9154820.8817020.821135
1323119890.9716520.9635980.9385970.9687170.9590550.9300100.9747900.9684550.947778
55312219890.9617920.9545440.9350020.9571020.9483430.9227590.9667050.9610400.947830
3397319890.9460310.9460310.9460310.9523440.9523440.9523440.9397600.9397600.939760
1152719890.9739680.9682540.9549210.9876390.9851670.9728060.9595300.9503920.936031
571419900.9141650.8792020.8171670.8904000.8480940.7795260.9381570.9106080.855168
2695719900.9839880.9827440.9804180.9894410.9894410.9887410.9781030.9755160.971435
50510819900.9872970.9870980.9823340.9892520.9888380.9834640.9854910.9854910.981291
4239019900.9938550.9938550.9895171.0000001.0000001.0000000.9885560.9885560.980478
countryyearAges[15-49]_All_grade1Ages[15-49]_All_grade2Ages[15-49]_All_grade3Ages[15-49]_Male_grade1Ages[15-49]_Male_grade2Ages[15-49]_Male_grade3Ages[15-49]_Female_grade1Ages[15-49]_Female_grade2Ages[15-49]_Female_grade3
2465220190.9724890.9639110.9422590.9679250.9568190.9286320.9772520.9713130.956481
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